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Single machine scheduling with learning effect considerations

delete2000-01-01
delete296
PRE
AI
T
T.C.E. Cheng *
G
Guoqing Wang
DOI：10.1023/A:1019216726076delete
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Abstract

Abstract

En 中文
In this paper we study a single machine scheduling problem in which the job processing times will decrease as a result of learning. A volume-dependent piecewise linear processing time function is used to model the learning effects. The objective is to minimize the maximum lateness. We first show that the problem is NP-hard in the strong sense and then identify two special cases which are polynomially solvable. We also propose two heuristics and analyse their worst-case performance.
Keywords:
scheduling
sequencing
learning
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Annals of Operations Research cover
Annals of Operations Research
IF:
4.5
Papers:
8.1K
Citations:
2.1W

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